The LIME method interprets individual model predictions based on linear assumptions and locally approximating the model around a given prediction but the correct definition of the neighborhood is unknown [1]}. LIME requires of human input to determine the correct kernel setting based on whether the explanations are coherent; however, this process is susceptible to mistakes  [2]}. Alvarez-Melis and Jaakkola showed that the explanations were very unstable given that for two very close points they varied greatly in a simulated setting and were often inconsistent with each other  [3]}.
